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Allosteric Effect of Nanobody Binding on Ligand-Specific Active States of the β2 Adrenergic Receptor.

ABSTRACT: Nanobody binding stabilizes G-protein-coupled receptors (GPCR) in a fully active state and modulates their affinity for bound ligands. However, the atomic-level basis for this allosteric regulation remains elusive. Here, we investigate the conformational changes induced by the binding of a nanobody (Nb80) on the active-like β2 adrenergic receptor (β2AR) via enhanced sampling molecular dynamics simulations. Dimensionality reduction analysis shows that Nb80 stabilizes structural features of the β2AR with an ∼14 Å outward movement of transmembrane helix 6 and a close proximity of transmembrane (TM) helices 5 and 7, and favors the fully active-like conformation of the receptor, independent of ligand binding, in contrast to the conditions under which no intracellular binding partner is bound, in which case the receptor is only stabilized in an intermediate-active state. This activation is supported by the residues located at hotspots located on TMs 5, 6, and 7, as shown by supervised machine learning methods. Besides, ligand-specific subtle differences in the conformations assumed by intracellular loop 2 and extracellular loop 2 are captured from the trajectories of various ligand-bound receptors in the presence of Nb80. Dynamic network analysis further reveals that Nb80 binding triggers tighter and stronger local communication networks between the Nb80 and the ligand-binding sites, primarily involving residues around ICL2 and the intracellular end of TM3, TM5, TM6, as well as ECL2, ECL3, and the extracellular ends of TM6 and TM7. In particular, we identify unique allosteric signal transmission mechanisms between the Nb80-binding site and the extracellular domains in conformations modulated by a full agonist, BI167107, and a G-protein-biased partial agonist, salmeterol, involving mainly TM1 and TM2, and TM5, respectively. Altogether, our results provide insights into the effect of intracellular binding partners on the GPCR activation mechanism, which should be taken into account in structure-based drug discovery.

SUBMITTER: Chen Y

PROVIDER: S-EPMC8715506 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThis study investigates the allosteric coupling that exists between the intra- and extracellular parts of human β2-adrenergic receptor (β2-AR), in the presence of the intracellular loop 3 (ICL3), which is missing in all crystallographic experiments and most of the simulation studies reported so far. Our recent 1 μs long MD run has revealed a transition to the so-called very inactive state of the receptor, in which ICL3 packed under the G protein's binding cavity and completely blocked its accessibility to G protein. Simultaneously, an outward tilt of transmembrane helix 5 (TM5) caused an expansion of the extracellular ligand-binding site. In the current study, we performed independent runs with a total duration of 4 μs to further investigate the very inactive state with packed ICL3 and the allosteric coupling event (three unrestrained runs and five runs with bond restraints at the ligand-binding site).ResultsIn all three independent unrestrained runs (each 500 ns long), ICL3 preserved its initially packed/closed conformation within the studied time frame, suggesting an inhibition of the receptor's activity. Specific bond restraints were later imposed between some key residues at the ligand-binding site, which have been experimentally determined to interact with the ligand. Restraining the binding site region to an open state facilitated ICL3 closure, whereas a relatively constrained/closed binding site hindered ICL3 packing. However, the reverse operation, i.e. opening of the packed ICL3, could not be realized by restraining the binding site region to a closed state. Thus, any attempt failed to free the ICL3 from its locked state due to the presence of persistent hydrogen bonds.ConclusionsOverall, our simulations indicated that starting with very inactive states, the receptor stayed almost irreversibly inhibited, which in turn decreased the overall mobility of the receptor. Bond restraints which represented the geometric restrictions caused by ligands of various sizes when bound at the ligand-binding site, induced the expected conformational changes in TM5, TM6 and consequently, ICL3. Still, once ICL3 was packed, the allosteric coupling became ineffective due to strong hydrogen bonds connecting ICL3 to the core of the receptor.

Project description:Metabotropic glutamate receptors (mGluRs) are G protein coupled receptors that play important roles in synaptic plasticity and other neuro-physiological and pathological processes. Allosteric mGluR ligands are particularly promising drug targets because of their modulatory effects--enhancing or suppressing the response of mGluRs to glutamate. The mechanism by which this modulation occurs is not known. Here, we propose the hypothesis that positive and negative modulators will differentially stabilize the active and inactive conformations of the receptors, respectively. To test this hypothesis, we have generated computational models of the transmembrane regions of different mGluR subtypes in two different conformations. The inactive conformation was modeled using the crystal structure of the inactive, dark state of rhodopsin as template and the active conformation was created based on a recent model of the light-activated state of rhodopsin. Ligands for which the nature of their allosteric effects on mGluRs is experimentally known were docked to the modeled mGluR structures using ArgusLab and Autodock softwares. We find that the allosteric ligand binding pockets of mGluRs are overlapping with the retinal binding pocket of rhodopsin, and that ligands have strong preferences for the active and inactive states depending on their modulatory nature. In 8 out of 14 cases (57%), the negative modulators bound the inactive conformations with significant preference using both docking programs, and 6 out of 9 cases (67%), the positive modulators bound the active conformations. Considering results by the individual programs only, even higher correlations were observed: 12/14 (86%) and 8/9 (89%) for ArgusLab and 10/14 (71%) and 7/9 (78%) for AutoDock. These findings strongly support the hypothesis that mGluR allosteric modulation occurs via stabilization of different conformations analogous to those identified in rhodopsin where they are induced by photochemical isomerization of the retinal ligand--despite the extensive differences in sequences between mGluRs and rhodopsin.

Project description:G protein-coupled receptors are involved in many biological processes, relaying the extracellular signal inside the cell. Signaling is regulated by the interactions between receptors and their ligands, it can be stimulated by agonists, or inhibited by antagonists or inverse agonists. The development of a new drug targeting a member of this family requires to take into account the pharmacological profile of the designed ligands in order to elicit the desired response. The structure-based virtual screening of chemical libraries may prioritize a specific class of ligands by combining docking results and ligand binding information provided by crystallographic structures. The performance of the method depends on the relevance of the structural data, in particular the conformation of the targeted site, the binding mode of the reference ligand, and the approach used to compare the interactions formed by the docked ligand with those formed by the reference ligand in the crystallographic structure. Here, we propose a new method based on the conformational dynamics of a single protein-ligand reference complex to improve the biased selection of ligands with specific pharmacological properties in a structure-based virtual screening exercise. Interactions patterns between a reference agonist and the receptor, here exemplified on the β2 adrenergic receptor, were extracted from molecular dynamics simulations of the agonist/receptor complex and encoded in graphs used to train a one-class machine learning classifier. Different conditions were tested: low to high affinity agonists, varying simulation duration, considering or ignoring hydrophobic contacts, and tuning of the classifier parametrization. The best models applied to post-process raw data from retrospective virtual screening obtained by docking of test libraries effectively filtered out irrelevant poses, discarding inactive and non-agonist ligands while identifying agonists. Taken together, our results suggest that consistency of the binding mode during the simulation is a key to the success of the method.

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Allosteric Effect of Nanobody Binding on Ligand-Specific Active States of the β2 Adrenergic Receptor.

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